The camera-based methods have been well investigated and have achieved high accuracy. However, privacy concerns should be considered for applications such as home surveillance.
Cameraless human segmentation methods have also been investigated to address privacy issues.
Wang et al. [1]} proposed a method for estimating human segmentation images, joint heatmaps, and part affinity fields using Wi-Fi signals.
They used three transmitting-receiving antenna pairs and thirty electromagnetic frequencies with five sequential samples.
The channel state information [2]} was analyzed to input networks.
The networks comprise upsampling blocks, residual convolutional blocks, U-Net, and downsampling blocks.
Although this method achieved privacy-friendly fine-grained person perception with Wi-Fi antennas and routers, the Wi-Fi signals are highly affected by the surrounding environment due to the multipath effect.
